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Hi. I am looking for someone who can give tuition in Hirshfeld surface analysis and crystal structure determination by single-crystal XRD. Is there anyone who can help me?
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Dear Alakbar Huseynzada many thanks for sharing this interesting technical question with the RG community. In my personal opinion both Hirshfeld surface analysis and crystal structure determination by single-crystal XRD require personal teaching and practical supervision. Both topics are too complex to be learnt online or by reading a few tutorials. If I were you I would contact colleagues at your institution who are experts in this field and ask if they give courses and can perhaps teach you individually. There are experts in Hirshfeld surface analysis and single-crystal X-ray diffraction at the Chemistry Department of Baku State University as can be seen by the following research article:
Crystal structure and Hirshfeld surface analysis of (3a SR ,6 RS ,6a SR ,7 RS ,11b SR ,11c RS )-2,2-dibenzyl-2,3,6a,11c-tetrahydro-1 H ,6 H ,7 H -3a,6:7,11b-diepoxydibenzo[ de , h ]isoquinolin-2-ium trifluoromethanesulfonate
This paper s freely available as public full text on RG. Thus please check with one of the colleagues at your department if they can help you.
Good luck with your work and best wishes, Frank Edelmann
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This advance from the machine learning method AlphaFold totally stopped me in my tracks. To me it seems that many things will change in how we do research and what research we do. Many biological and medical questions can now be better addressed from the structural and mechanistic perspective. This seems likely to enable many rapid advances in things such as precision molecular medicine.
As noted in their Nature paper, accurate models will enable a wide range of applications: from homology search and putative function assignment to molecular replacement structure determinations and druggable pocket detection for the human proteome.
How do you imagine that we will harness this information of human protein folds for research and medicine?
News
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Bhaskar Ganguly rightly complains about AlphaFold swooping in to steal to fun of folding with logical inferences. However I suggest that we can take this to the next level which is all about conformations (allostery) and complexes (interfaces and communication/regulation). In a sense there is more juice here where the complexes and conformations are more likely to speak to activity, regulation, and function. Why not jump this fold level and go bigger?
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I am currently working on a project on cryoEM single particle analysis of protein complexes. Though using HPLC size chromotography can separate the complexes and individual subunits, the structure is not homogeneous tested by negative staining. It might be due to the buffer used. However, how to choose the buffer? and how to access the stability of the protein complexes? Any suggestion is welcome.
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Unfortunately, things like glycerol or other additive that may stabilize a protein complex would add background to the images. A diagnosis for assessing the apparent heterogeneity stemming from the instability of the protein complex, not due to insufficient puification, is to check the distribultion from your 2D class-average images. However, since Relion has attractor effect---your complex vs complex minus a small subunit can be merged into the same class, we thus recommend ISAC or IMAGIC to do so. By the way, negative stain is tricky because uranyl acetate is acid (uranyl formate is neutral but the contrast is lower) and the supporting carbon would do something adverse. We will update you with other approaches that we are testing regarding this critical issues soon.
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I'm working in the field of plants, isolation, and structure determination of biologically active natural compounds.
I need NMR of proton, carbon-13, 2D,...
Any suggestions in this regard; free book, course, or support is valuable.
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Dear Alexander Sinko thank you for your interesting technical question. Ideally, the person at your institution who runs the NMR spectrometer will give you a personal instruction or perhaps offers a course. It's not a matter of half an hour to learn NMR spectroscopy, especially when it comes to characterizing complicated biologically active natural compounds.
On the general internet you can easily find a variety of free courses and tutorials when you search for "Introduction to NMR spectroscopy", including YouTube videos.
For example, please have a look at the following useful links:
INTRODUCTION TO NMR SPECTROSCOPY
This rather comprehensive introduction can be freely downloaded as pdf file.
Introduction to Nuclear Magnetic Resonance
Basic Introduction to NMR Spectroscopy
and many others.
Good luck and please stay safe and healthy! 👍
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My question is about the Debye-Scherrer equation, which contains the constant K, according to my knowledge 0.9 is used for cubic structure, however, my sample has a hexagonal structure (determined by the XRD results), so I should look for the K value more appropriated for this structure.
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There is no such thing as the Debye-Scherrer equation. There is a Debye-Scherrer camera, a Scherrer equation, and a Debye model, but the 'Debye-Scherrer equation' does not exist.
The Scherrer equation only deals with line broadening which can come from (nano) size, strain, and instrument. The Williamson-Hall approach is a better on.
Just quote the value of K you use. The model is so simple (and poor) that anyone else can use another factor and recalculate. There's a crystallite size distribution and Scherrer only produces a single value. so whether you use 0.8 or 1.0 (based on debatable theory) there will be bigger variation from sample heterogeneity.
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I need to determine the open formula of our complex, presumably consisting of sodium tungstate Na2WO4 and aluminum sulfate Al2 (SO4) 3. Our problem is that with an increase in the concentration of the solution above 10 ^ -3 mol / l, the properties and possibly the structure change and it is impossible to achieve a stable monosalt for determining the structure. We need an exact formula to be determined inside the solution. I am waiting for your answers and terms of cooperation.
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Mr. Bagdasaryan,
The method of mass spectrometry within the framework of our own-authored (to me and my co-author's according to the authorship shown below) innovative stochastic dynamic theory for quantification of experimental variables has capability of providing exact 3D molecular and electronic structures of the molecules, respectively, ions in solution.
Please, consider references [1,2].
[1] Electrospray ionization mass spectrometric solvate cluster and multiply charged ions: a stochastic dynamic approach to 3D structural analysis
Bojidarka Ivanova, Michael Spiteller
SN Applied Sciences; volume 2, Article number: 731 (2020)
[2] Bojidarka Ivanova und Michael Spiteller
A stochastic dynamic mass spectrometric diffusion method and its application to 3D structural analysis of the analytes; Reviews in Analytical Chemistry, 38 (2019) 20190003; DOI: https://doi.org/10.1515/revac-2019-0003
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Dear community,
As far as I understand, negative density features point at stuff that is in the model, but not supported by experimental data.
However, in many cases (e.g. attached image), when you visualize the densities, there are negative (red) density blobs not containing any atoms inside. Just empty space inside. There is nothing in the model in those regions of space. How it should be interpreted?
Could you tell me please what I am missing?
Would be grateful for any help,
Best wishes,
Aliaksei
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Even in a well-refined structure some residual difference density is always expected. In this case the small negative peak could have to do with imperfect bulk solvent modelling/scaling. I wouldn't worry about it too much, it's very minor in this case. The negative difference density at the carboxylic acid group of the glutamate however could be indicative of radiation damage; in that case refining with lower occupancy can be a solution. Other tell-tale signals for radiation damage are e.g. cleaved Cys-Cys disulfid bonds. HTH, Jonathan.
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Please aid with software as well as strategies in order to get X-ray structure in a similar fashion to single crystal X-ray refinement. We have D2 Phaser-Bruker XRD instrument to obtain PXRD data available. Thanks in advance
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EXPO2014 (http://www.ba.ic.cnr.it/softwareic/expo/) is good software for structural determination and rietveld refinement. It is easy to use and has a good manual.
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The individual responds to the stimuli with the help of cognitive structures and experiences.
The quantity and quality of such knowledge structures determines the type and quantity of the response.
We need to modify, improve and develop knowledge structures.
How do?
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Any answer I would provide would be similar to that and have the same main points.
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In circular dichroism analysis, I have used k2d2 server for estimation of alpha helix and beta strand but how i can determine the qualities of such estimation by graphically or numerically using error interval.
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Dear Rohit,
I’m not completely sure whether I understand your question correctly. Since in the original paper describing the K2D2 method:
It is stated clearly that the performance of K2D2 is (as common with tools like this) measured by comparing real and predicted values, by means of the so-called Pearson correlation coefficient (r) and the root mean square deviation (RMSD). Averages of r of 0.8-.9 or higher and average values of RMSD of 0.1 or lower can be considered as pretty good.
However the program itself gives the ‘real’ CD spectrum and the predicted one so it is clear by just visual inspection whether the prediction is rather good or not.
So there are two ways by which you can communicate your prediction: either visual or by mentioning the r- and RMSD values.
Hope this answers your question.
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Dear colleague,
I am going to study the occupations of Wyckoff sites for intermetallic compounds based on single crystals prepared under different conditions. I want to know which code, among Crystals, WingX, Shelx, etc. is the best for this purpose?
Thank you very much in advance.
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Dear Fang,
GSAS is most classical one, but needs more time to fit your data.
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To expand upon the question, I am currently studying a material for which I need to carry out an ISIF=3 relaxation. I keep ISYM=2, which is the default value, and the symmetry of the structure is determined a the beginning of the run to be C2, which is what I expect it to be. This is pretty low symmetry, but still a symmetry nonetheless. Over the course of the ISIF=3 relaxation, this symmetry is eventually broken, and subsequent ISIF=3 continuation runs tell me my structure is now at C1 symmetry instead. This is not the desired result.
Why is this happening? In my experience, VASP is pretty good about maintaining the symmetry as long as it is determined to be correct at the beginning. In the past, I've dealt with bulk wurtzite CdS and CdSe, which both have fairly high symmetry, and all ISIF=3 relaxations of those materials preserved the correct symmetry. But for some reason, my current C2 structure can't keep to that during relaxation.
Any help would be greatly appreciated.
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Peyton Cline As a general rule, if you allow shape/volume and ions to relax, you do not have any constraints in your simulations, so nothing 'preserving' the initial symmetry. When you relax your initial structure, and this starting configuration is close (in configuration space) to a local energy minimum, you usually reach this minimum, thus the symmetry is preserved. But this works only because you start very close to this local minimum, and also there is usually an energy barrier between this minimum and another one of lower energy. Relaxing the system (using conjugate gradients or Newton-based approaches), you can not overcome the energy barrier. Then I suppose that in your case, your target minimum is not a minimum, or your starting configuration is too far from this minimum (so you fall down in the lower energy one).
Just to mention, there are also cases when a change between two configurations of different symmetries will be prevented. You simply need to use a supercell that can represent one symmetry but not the other (not enough atoms for instance).
I hope it is a bit more clear...
For your specific problem, I do not have any solutions sorry. The best advice I could give is to try to find papers where such calculations have been done, to see if there is some tricky issues with this material in DFT.
Best,
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ICSD and springer both are paid database. Is there any open access database for crystal structure determination?
Thanks in advance!
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great - very welcome
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Hi, I was searching the polarity of Eicosapentaenoic acid and Docosahexaenoic acid and I found a site online that said most hydrocarbons were non-polar. Also I found some examples using Lewis structure to determine the polarity for simple structure of some compunds but not hydrocarbons.
Is there a set of rules to determine the polarity of icosapentaenoic acid and Docosahexaenoic acid?
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Hi Saif,
Just some info. for you. I separated lipids by TLC based on their polarity. As far as I know, DHA and EPA are less polar than diacylglycerol (DAG) but more polar than triacylglycerol. DAG is slightly polar because it has only one -OH group and a lot hydrocarbons. TAG is neutral. So free fatty acids are close to neutral or very slightly polar as it has only one COOH.
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I am currently working on reviving an XRD machine.it is SMART APEX II form bruker.
the x-ray source is Molybdenum.
The problem I am facing now is that the main application is protein x-ray crystallography.Is there a way to use the mo x-ray source with protein structure determination?
kind regards,
Moustady
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Yes of course , you are allowed to use my answer(s).
But I am not member of linkedin.
However you may use your (RG) access to my RG homepage.
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I am unfamiliar to how MALDI-TOF MS can identify protein structure. I have read websites indicating that it can be done. However, I would like to know of how accurate are the results of MALDI-TOF MS vs. Xray crystallography. Does anyone have references that I may read regarding use of MALDI-TOF MS for protein structure determination? Thanks in advance.
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MALDI-TOF MS can tell peptide molecular weight, peptide sequences, modifications etc, which in return may suggest the protein interactions if cross-linking sample used. The MALDI-TOF MS results sometime could be helpful for interpreting assays. It is far too much if someone claims that MALDI-TOF MS can determine protein structure. Currently protein structure determination is done by crystallography, EM, or NMR. 
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I am working with DNA-protein complex crystallization . I have tried fragments varying in length from 35 bp to 27 bp. DNA is specific in terms of affinity to protein. I am getting crystals with all the fragments but they are not diffracting . They form gelatinous like morphology when disturbed. How to improve for diffraction?
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HI,
Protein-DNA complexes can be tough to crystallize.  The fact that your crystals are becoming jelly-like reminds me of something that happened with my protein-DNA complex.  I worked with a nuclease, and found that cleavage was happening slowly in the crystal over time.  Crystals shot within a few days of formation diffracted well, but those harvested a week or two later were gelatinous (like a gummy candy) and didn't diffract.  This was because the DNA conformation was central to maintaining crystal contacts.  It would be helpful if you could describe the protein-DNA complex you are going after.  I think the first thing you should do is confirm that the protein-DNA complexes are forming in solution before crystallization: Appu's suggestion of using SEC_MALS is an excellent one.  I would also harvest your non-diffractive crystals, and run them on a gel to check if the crystals are your complex, and if your DNA is intact.  Playing with DNA length and sequence at the ends will be helpful, and you may also want to experiment with using sticky ends or backbone modifications that prevent hydrolysis, such as a phosphorothioate.  I added a phosphorothioate modification at each of the 3' and 5' ends: it disrupted a crystal contact for my P21212 crystals but that led to new interactions that ended up improving symmetry and resolution.  I have several colleagues who have found sticky ends or alternate DNA-structures to be helpful.  
Please follow-up to let us know if our suggestions help, or to provide some information we can use to help you.  Hang in there: I had a colleague who used more than 35 different Holliday junction substrates before he found the right one.
Happy Crystal Hunting!
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When FeCl2/FeCl3 is added to chalcones, a reddish-brown colour appears, however, the equations for this reaction reported in the literature always show the chalcone as a charge balancing ion, rather than a ligand coordinated to the metal centre. So, what type of interaction exists in this case between Fe and the chalcone? Is it ionic or a coordinate bond?
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Dear Mohammed,
Find in attach, Supplementary Material for Chemical Communications
This journal is © The Royal Society of Chemistry 2003
Electronic supplementary information entitled " Efficient and Inexpensive Catalyst System for the Aza-Michael Reactions of Enones with Carbamates"
You find inside:
UV analysis of the
CH2Cl2 or CH3CN solution of chalcone with this catalytic system (Me3SiCl and FeCl3·6H2O) to
confirm the possibility in the present reaction system. On the other hand, UV analysis of the
interaction of enones and Brønsted acid (aq. HBF4 ), Transition metal salts ( Cu(OTf)2, PdCl2)
were also be performed. These results showed in figure 1 and figure 2.
Figure 1:
In CH2Cl2, 1# the solution of chalcone; 2# the solution of chalcone and FeCl3·6H2O; 3# the solution of chalcone, Me3SiCl and FeCl3·6H2O.
Figure 2:
In CH3CN,4# the solution of chalcone and aq. HBF4; 5# the solution of chalcone and Cu(OTf)2;
6# the solution of chalcone and PdCl2(CH3CN)2; 7# the solution of chalcone, Me3SiCl and
FeCl3·6H2O.
Reaction of chalcones with FeCl3. What is the structure of the resulting complex? - ResearchGate. Available from: https://www.researchgate.net/post/Reaction_of_chalcones_with_FeCl3_What_is_the_structure_of_the_resulting_complex#57cd58d55b4952a6ef4e8183 [accessed Sep 5, 2016].
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The unit cell of a magnetic structure is determined by the propagation vector. In my opinion, a propagation vector of (001) should give the same result of (000). But I find some reports mentioned that the propagation vector for their structures are (001) or (010) or (100). What is the difference between (000) and (001)?
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That depends on the crystal structure.
For example,  in a simple cubic (SC) crystal (000) and (001) are identical. Along the (00L0 direction the Brillouin zone boundary is at (00 1/2).
In a body-centered cubic (BCC) crystal (001) is "forbidden" because the conventional (cubic) unit cell contains two primitive unit cells. The Brillouin zone boundary is at (001), and the next Brillouin zone center is at (002). In that case a (001) magnetic structure is an antiferromagnet where the body center point in the opposite direction to the corner of the conventional unit cell.
This is also true for the I4/mmm structure of the ThCr2Si2 structure type you mentioned in another question - my simple picture applies to the Th site.
In diffraction experiments you see (00 2n+1) peaks arising in the magnetically ordered phase, but not in the paramagnetic phase.
(100) and (010) are the same as (001) in this case, as (101) is a reciprocal lattice vector.
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I have prepared a nanocrystals which don't have reference data. I have collected the PXRD data for both bulk and the nanocrystal. In my manuscript, I have compare these two data. I want to know its crystal system.
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You need to start with indexing of diffraction peaks. For example using FOX software:
The following steps are specific for the case.
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I am writing a review paper on X-ray crystallography, I need help in following fields: 
  • Analysis of diffraction pattern,
  • Electron density map,
  • Structure determination and refinement.
Regards
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There is also a distinct difference between small-molecule, powder, and macromolecular crystallography. The tools they use are very different. I work in macromolecular crystallography and I mostly use XDS and tools from the CCP4 suite, most notably REFMAC and COOT. Buster is also very good and PDB_REDO is also becoming quite popular.
Now at the risk of sounding cynical: if you need to ask these questions, why are you writing this review? 
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I have sent my crystal for synchrotron and now I have diffraction images. I want to start the data processing. It is my first time and I need to know the step by step protocols (for MR or SeMet) and the needed software for each steps from diffraction images until pdb file submitting.
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Welcome to the club of structure hunters !!
Your question is a very general one implementing thousands of sub questions and strategies and several possible programs of data processing for each step. Better find somebody around you who knows and has the time to explain details for your first structure as well as for a the dozen to come. 
the steps are :
1. LOOK with great attention your images
2. INDEX your data and find the adequate SPACE GROUP ...
3. INTEGRATE your data considering this SPACE GROUP
4. IMPORT & SCALE  the integrated data within a data processing program (PHENIX, CCP4, ...etc)
5. PHASE the data by MOLECULAR REPLACEMENT or EXPERIMENTAL PHASING and find a molecular MODEL
6. REFINE the molecular MODEL
7. DEPOSITE to the pdb...
Each protein is a new adventure with new problems and new desicions and strategies to apply. And it's an amazing job I tell you..!
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Is there any software available online? May you kindly suggest some? Thank you.
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thank you
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Can any university accept outside students doing attachment for 1 week and analysis on structure solution using TOPAS (Bruker software)?
We can discuss a fee later.
Regards,
XRD Department, National University of Malaysia.
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To be more specific, what kind of experiments would you perform to get structural constraints data for small, medium and large proteins? I am struggling to find a paper that solely talks about this without going to the details of each technique. I just want to know what the experiments does and what kind of information do you get for the experiment being done on different size of proteins. Any papers that you could suggest would be much appreciated! Thank you in advance
Updated response:
As commenters pointed out, I realised my questions are too broad. So I am talking about soluble proteins using solution state NMR technique. 
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Hi Faiz,
You have asked a very broad question that is not going to be covered by a single paper. I would suggest the following book to start.
Structural Biology: Practical NMR Applications
by Quincy Teng.
All the best
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My plan is to run a MD simulation, with the NMR derived constraints from the closed to the intermediate structure. However, not having a NMR background, I don't know how to convert Hydrogen exchange data into distance constraints.
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You can try the method in here to convert hydrogen exchange rates to constraints for molecular dynamics
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I want to calculate secondary structure of the proteins by FTIR.
To do so I recorded the Primary spectra of my protein. In order to get more resolution of the peaks I am doing deconvolution followed by curve fitting of the primary spectra. In doing so I have found the following problems. I am using OPUS software provide by Brooker.
For deconvolution
1. I do not understand how I can avoid over deconvolution of primary spectra. i.e. how to know the selected values for bandwidth and noise suppression factor are correct. Just by looking the spectra while deciding these values or is another statistical method is available which could tell the reliability of deconvoluted spectra?
2. I have selected amide 1 region for the secondary structure determination. (1700 cm-1 to 1600cm-1). The baseline was corrected only within this region and proceeded for deconvolution. While performing deconvolution I observe that some of the region of spectra, ma be  from 1686 to 1670cm-1, were going to a more negative value than at 1700cm-1 which starts from zero. This is giving me problems while performing curve fitting.
For Curve fitting.
1. I determine the secondary derivative of my deconvoluted spectra and select the peak at particular wavenumber.
2. in the opus software one needs to give another two parameter
a. Intensity at particular wave number
b. width
I don't have a problem in selecting value for intensity, but which value should be put in the width column ?.
3. After doing curve fitting it will give the value of RMS. I know the meaning of RMS, but how can I know what is the acceptable limit for this value. After every fit it will give the RMS value which is always different. I came to know from the literature that RMS value should be low. But how low?
Thank You
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Hi Mangesh,
I'm also an Opus user - but whatever software you use, please don't accept it as a "black box", make sure you really understand what it's doing. If necessary, use a mathematics software like Matlab or Igor Pro to check that the calculation procedure is according to your wishes. Two points in particular:
1. How many bands should you use to fit? It's not correct to use the quality of the fit (i.e. residual RMS error) to determine this, because the fit quality will always increase with increasing number of bands ad infinitum, regardless of whether there's any connection with the actual number of bands present in your data - this is simply the difference between mathematics and real life.
So you need an empirical determination of how many peaks your data really justifies. Two alternative ways to do this:
a) Take the second derivative of your data and count the minima. See the 3 attached JPGs, which illustrate how this works for a single synthetic Gauss peak and for two peaks with and without overlap. Note that when the two peaks are near to each other, the 2nd derivative shows the smaller peak shifted from its true position - but probably still good enough as an initial estimate for the iterative fitting procedure. This problem disappears when the peaks are far apart, but a spurious additional minimum appears in between due to the interaction of the side bands. In spite of these potential issues, at least you're using an empirical procedure to count the bands which others can reproduce.
b) Fit with 1 peak, then 2 peaks, then 3 peaks, etc., watching how the residual RMS error decreases with each step. Decide in advance what you consider to be a significant improvement, e.g. 5%. Stop adding peaks when the improvement in the RMS error value falls below this threshold. What you're saying here is that you're describing your data with this number of peaks because the data does not contain significant evidence for any more peaks than that - as a scientist I find that intellectually satisfying.
2. The second important issue is to be careful of what you're doing with the baseline subtraction and spectral region cutoff. Are you sure that it's really some kind of baseline artefact underlying your amide I data, and not the flanks of peaks outside that cutoff range, especially at the 1600/cm end? Look again at my "2 peaks near.jpg" example and imagine subtracting a straight "baseline" from -2 to +2, then fitting just that region. The remainder after subtraction would no longer be Gaussian curves and the fit will doing something arbitrary and wrong to try explaining the shape of the curve. This may well explain why you're getting negative peaks.
The solution? Ideally, you do the experiment carefully and properly so that the data has no baseline artefact. If that's not possible, you understand the cause of the artifact - scattering? residual water? - and describe it with the correct equation. Assume the peaks towards the edges of your selected spectral region will always come out wrong because of the cutoff, therefore fit from 1500 to 1800/cm and then discard the peaks outside the region of interest.    
Cheers,
David
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Is it possible to calculate the band structure from data of single crystal XRD?
Data is in the form of CIF file.
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It really depends on what calculation way you want to use. For the tight binding lmto model calculation, the cif info is all that you need:
For other programs, i dont know.
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I want to know about the mosaicity in macromolecular crystallography as a novice. How does it impact the structure determination of the protein?
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When you think of a crystal, you might imagine all the unit cells lined up perfectly. In reality it looks more like a Roman mosaic, with blocks of unit cells with defects between. The effect on the diffraction pattern is to broaden the diffraction spot profiles. Some mosaicity is a good thing, else the peaks would be too sharp to measure (this is much more likely in a small molecule crystal!). A high mosaic spread (high mosaicity) can cause problems with spot overlap.
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I have been reading up on the TGR5 receptor and how it could be used in treatment of various aspects of metabolic syndrome, however, a crystal structure has not yet been found and through my reading I cannot find why, so I was wondering if anybody knew and what studies could be done in order to solve it?
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the reason for no structures is that it is a membrane protein and currently there are only a few hundred membrane protein structures compared to several thousand soluble proteins. Also as a class of MP the GPCRs are particularly difficult probably because they are less stable in detergent than other membrane proteins, In fact there have been consortia set up to look at the structural genomics of GPCRs because they are recognized as difficult structures to obtain, See Lundstrom in Trends Biotechnol, 2005, 23(2), 103.
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Distance information provides powerful insights for macromolecular structure determination and analysis. What are the promising, current and emerging approaches for this method?
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Yes I am quite interested in reducing false positives in distance geometry based structures. I am less interested in using distance geometry to filter possible solutions.
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I want to make the structural resolution of a condensed phosphate hydrate and I have the laboratory data as datafile.dat, I already started working with DICVOL and TREOR, and they give me the same thing parameters, but I have no idea about the corresponding isotype to start work with Fullprof, so I think i must work with FOX or Expo
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FOX and EXPO both are the great programs, but FOX (and the real-space methods) is less-sensitive for the lower quality of diffraction data. Anyway, if you have a heavy atom in the unit cell it usually helps in both methods. Finding the right unit cell and chemical composition is a big part of success. Personally, I have never managed to solve any new structure using EXPO, but dozens with FOX. Good luck!
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I have cloned my domain in an expression vector and forgot to include stop codon at its 3' end and six more aminoacids were included from the vector.
If up to what no of residues from vector?
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PDB will accept it. it is a non-native cloning artefact. Just include it and describe the additional residues as such. Who knows it might not have crystallised without it!
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I am solving a structure of which I have X-ray data up to 1.5 A resolution. However, there are not so many spots in the highest resolution region, so that when I solve the structure (with a good model I have from a closely related protein) everything looks very good in terms of density fitting and stats, but the overall R and freeR factors are still quite high (0.23 and 0.26).
The only way I found to lower the R factors is to discard the higher res data. For instance, if I don't consider the data <1.9 my R factor decrease by 2-3%, and if I go down to 2.1 A my R factor goes below 0.20, but the density around my residues is not so good anymore. Any suggestion on what is best to do in this situation? Would you prefer solving a structure with lower R factors and lower resolution, or higher resolution but higher R factors?
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The aim of refinement is not to reduce the R-factors. In any case, when solving a structure (for example using anomalous scattering), it is preferable to process the data so that the best possible data are obtained. When refining a structure that was solved, then one can go back to the initial frames with a view to extract as much information (but not integrate noise thinking the noise are Bragg peaks). For this, a couple of tools are useful: the novel statistical indicator CC1/2 (produced by XDS and Aimless) plus a plot of the Rsym as a function of resolution - there is an inflexion point where the curve shoots up, an indication of the high resolution limit.
But again, the aim of refinement is not to reduce the R-factors. The aim is to generate a model that fits at best all available data (including the biochemical data, the restraints obtained from structural libraries etc)
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In order to deposit a protein structure on the PDB database the file needs to have a TER card at the end of the chain.
In the past I have added them manually in the PDB file and changed the number of the atoms accordingly, but it is a pain and, particularly if the protein has more than 1 chain, very time consuming!
Do you know of any utilities that can add the TER cards and update the atom numbers automatically?
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Matteo: "genter is the option to add TER records in pdbcur
in a command line after setup the ccp4 environment:
pdbcur xyzin in.pdb xyzout out.pdb <<EOF
genter
EOF